Nathalie JustExpertise
MRIfMRIfMRSPreclinicalAnimal PhysiologyOptogenetics, Chemogenetics
Travail en cours
fMRS, Deuterium Imaging and Hyperpolarization
Enseignement et PhD Cours Advanced biomedical imaging methods and instrumentation PHYS-719 The main goal of this course is to give the student a solid introduction into approaches, methods, and instrumentation used in biomedical research. A major focus is on Magnetic Resonance Imaging (MRI) and related methods, but other imaging modalities will be increa
Friedhelm Christoph HummelExpertise
Stroke recoveryHealthy AgingMotor ControlMotor LearningCognitive ControlNeuroplasticityNon-invasive Brain StimulationStructural and functional NeuroimagingConnectivity
Enseignement et PhD Doctorant·es actuel·les Maria Ploumitsakou, Simona Losacco, Fabienne Windel, Andrea Protani, Stavroula Skarvelaki, Wei Chung Hsu, Rebecca Jane Jones, Beatrice Lugli, Thomas Paul, Paul de Fontenay, Michele Di Ponzio, Léa Kim-mi Ho Dac, Dong Jin Sung, Andrea Nuti, Greta Carnevali A dirigé les thèses EPFL de Rober
Guillaume Romain ObozinskiGuillaume Obozinski est Chef Data Scientist Adjoint au Swiss Data Science Center. Il a reçu le diplôme de doctorat en Statistiques de l'Université de Californie à Berkeley en 2009. Post-doc puis chercheur dans les équipes Willow et Sierra à l'INRIA / Ecole Normale Supérieure à Paris jusqu'en 2012, il a été chercheur à l'Ecole des Ponts ParisTech à Paris jusqu'en 2018. Ses domaines d'expertise sont principalement en apprentissage automatique, en statistique et en optimisation. Il a travaillé au fil du temps sur les méthodes d'apprentissage parcimonieux, les techniques d'optimisation pour l'apprentissage, les modèles graphiques probabilistes, l'apprentissage relationnel et les représentations vectorielles sémantiques. Il est intéressé par l'application de ces techniques à tous les domaines des data sciences, depuis la biologie computationnelle à l'analyse automatique d'images.
Rolf GruetterAwards:
1999 Young Investigator Award Plenary Lectureship
, International Society for Neurochemistry
2011 Fellow
, ESMRMB
2011 Teaching Award
, Section Sciences de la Vie, EPFL
Pascal FrossardTeaching & PhD PhD Students Yiming Qin, Alba Carballo Castro, Elisa Messori, Ke Wang, Sevda Ögüt, Tuna Alikasifoglu, William Cappelletti, Manuel Madeira, Mahdi Amiri, Ortal Yona Senouf, Vasiliki Rizou, Cem Bilaloglu, Abdellah Rahmani, Amel Abdelraheem, Jérémy Jean Philippe Baffou, Adam Hazimeh, Vincent Jung, Yike Zhao Past EPFL PhD Students Dan Jurca, Jean-Paul Wagner, Ivana Radulovic, Ivana Tosic, Effrosyni Kokiopoulou, Zafer Arican, Vijayaraghavan Thirumalai, Tamara Tosic, Eirina Bourtsoulatze, Elif Vur
Wulfram GerstnerWulfram Gerstner is Director of the Laboratory of Computational Neuroscience LCN at the EPFL. His research in computational neuroscience concentrates on models of spiking neurons and spike-timing dependent plasticity, on the problem of neuronal coding in single neurons and populations, as well as on the link between biologically plausible learning rules and behavioral manifestations of learning. He teaches courses for Physicists, Computer Scientists, Mathematicians, and Life Scientists at the EPFL. After studies of Physics in Tübingen and at the Ludwig-Maximilians-University Munich (Master 1989), Wulfram Gerstner spent a year as a visiting researcher in Berkeley. He received his PhD in theoretical physics from the Technical University Munich in 1993 with a thesis on associative memory and dynamics in networks of spiking neurons. After short postdoctoral stays at Brandeis University and the Technical University of Munich, he joined the EPFL in 1996 as assistant professor. Promoted to Associate Professor with tenure in February 2001, he is since August 2006 a full professor with double appointment in the School of Computer and Communication Sciences and the School of Life Sciences. Wulfram Gerstner has been invited speaker at numerous international conferences and workshops. He has served on the editorial board of the Journal of Neuroscience, Network: Computation in Neural Systems', Journal of Computational Neuroscience', and `Science'.
Stephan MorgenthalerEDUCATION
Ph.D., Statistics, Princeton University, Princeton, 1983
Diplôme, Mathématiques, Ecole polytechnique fédérale de Zurich, 1979
CARRIÈRE ACADEMIQUE
Professeur de statistique appliquée, EPFL, 1991-présent
Professeur extraordinaire, statistique appliquée, EPFL, 1988-1991
Professeur associé, statistique, Yale University, 1987-1988
Professeur assistant, statistique, Yale University, 1984-1987
Instructor, mathématiques, Massachusetts Institute of Technology, 1983-1984
Pierre VandergheynstPierre Vandergheynst received the M.S. degree in physics and the Ph.D. degree in mathematical physics from the Université catholique de Louvain, Louvain-la-Neuve, Belgium, in 1995 and 1998, respectively. From 1998 to 2001, he was a Postdoctoral Researcher with the Signal Processing Laboratory, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland. He was Assistant Professor at EPFL (2002-2007), where he is now a Full Professor of Electrical Engineering and, by courtesy, of Computer and Communication Sciences. As of 2015, Prof. Vandergheynst serves as EPFL’s Vice-Provost for Education. His research focuses on harmonic analysis, sparse approximations and mathematical data processing in general with applications covering signal, image and high dimensional data processing, computer vision, machine learning, data science and graph-based data processing. He was co-Editor-in-Chief of Signal Processing (2002-2006), Associate Editor of the IEEE Transactions on Signal Processing (2007-2011), the flagship journal of the signal processing community and currently serves as Associate Editor of Computer Vision and Image Understanding and SIAM Imaging Sciences. He has been on the Technical Committee of various conferences, serves on the steering committee of the SPARS workshop and was co-General Chairman of the EUSIPCO 2008 conference. Pierre Vandergheynst is the author or co-author of more than 70 journal papers, one monograph and several book chapters. He has received two IEEE best paper awards. Professor Vandergheynst is a laureate of the Apple 2007 ARTS award and of the 2009-2010 De Boelpaepe prize of the Royal Academy of Sciences of Belgium.
